Customer segmentation using K-means
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
| Հիմնական հեղինակներ: | , , , , |
|---|---|
| Այլ հեղինակներ: | |
| Ձևաչափ: | Թեզիս |
| Լեզու: | en_US |
| Հրապարակվել է: |
Brac University
2022
|
| Խորագրեր: | |
| Առցանց հասանելիություն: | http://hdl.handle.net/10361/17617 |
| id |
10361-17617 |
|---|---|
| record_format |
dspace |
| spelling |
10361-176172022-11-24T21:01:36Z Customer segmentation using K-means Mahdee, Nafis Shourav, Ishrak Rahman Tabassum, Tasneem Nur, Eman Md Amir, Hamza Howlader Rasel, Annajiat Alim Department of Computer Science and Engineering, Brac University Segmentation Customer segmentation Clustering K-means RFM LRFM PCA Data mining Machine learning Natural computation--Congresses. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 35-37). Sales Maximization is a critical aspect of operating any business. Our thesis aims to help businesses to probe deep into their market reach as we group customers us ing the customer segmentation approach. Our dataset is formed based on customer behavior and purchase history. The outcome of this organized study is expected to yield powerful insights in predicting consumer purchasing behavior and related pat terns. Using the K-means algorithm, we analyze real-time transactional and retail datasets. The analyzed data forecasts purchasing patterns and behavior of cus tomers. This study uses the RMF (Recency, Frequency Monetary), LRFM (Length, Recency, Frequency, Monetary), and PCA model deploying K-means on a dataset. The results thus obtained concerning sales transactions are compared with multiple parameters like Sales Recency, Sales Frequency, and Sales Volume. Nafis Mahdee Ishrak Rahman Shourav Tasneem Tabassum Eman Nur Md Amir Hamza Howlader B. Computer Science and Engineering 2022-11-24T08:40:11Z 2022-11-24T08:40:11Z 2022 2022-05 Thesis http://hdl.handle.net/10361/17617 en_US Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 37 Pages ID: 18301035 ID: 18101664 ID: 17101219 ID: 17101375 ID: 17101528 application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
en_US |
| topic |
Segmentation Customer segmentation Clustering K-means RFM LRFM PCA Data mining Machine learning Natural computation--Congresses. |
| spellingShingle |
Segmentation Customer segmentation Clustering K-means RFM LRFM PCA Data mining Machine learning Natural computation--Congresses. Mahdee, Nafis Shourav, Ishrak Rahman Tabassum, Tasneem Nur, Eman Md Amir, Hamza Howlader Customer segmentation using K-means |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. |
| author2 |
Rasel, Annajiat Alim |
| author_facet |
Rasel, Annajiat Alim Mahdee, Nafis Shourav, Ishrak Rahman Tabassum, Tasneem Nur, Eman Md Amir, Hamza Howlader |
| format |
Thesis |
| author |
Mahdee, Nafis Shourav, Ishrak Rahman Tabassum, Tasneem Nur, Eman Md Amir, Hamza Howlader |
| author_sort |
Mahdee, Nafis |
| title |
Customer segmentation using K-means |
| title_short |
Customer segmentation using K-means |
| title_full |
Customer segmentation using K-means |
| title_fullStr |
Customer segmentation using K-means |
| title_full_unstemmed |
Customer segmentation using K-means |
| title_sort |
customer segmentation using k-means |
| publisher |
Brac University |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10361/17617 |
| work_keys_str_mv |
AT mahdeenafis customersegmentationusingkmeans AT shouravishrakrahman customersegmentationusingkmeans AT tabassumtasneem customersegmentationusingkmeans AT nureman customersegmentationusingkmeans AT mdamirhamzahowlader customersegmentationusingkmeans |
| _version_ |
1814307204426104832 |